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Can we trust shoestring evaluations ?

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  • Ravallion, Martin

Abstract

Many more impact evaluations could be done, and at lower unit cost, if evaluators could avoid the need for baseline data using objective socio-economic surveys and rely instead on retrospective subjective questions on how outcomes have changed, asked post-intervention. But would the results be reliable? This paper tests a rapid-appraisal,"shoestring,"method using subjective recall for welfare changes. The recall data were collected at the end of a full-scale evaluation of a large poor-area development program in China. Qualitative recalls of how living standards have changed are found to provide only weak and biased signals of the changes in consumption as measured from contemporaneous surveys. Importantly, the shoestring method was unable to correct for the selective placement of the program favoring poor villages. The results of this case study are not encouraging for future applications of the shoestring method, although similar tests are needed in other settings.

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Bibliographic Info

Paper provided by The World Bank in its series Policy Research Working Paper Series with number 5983.

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Date of creation: 01 Mar 2012
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Handle: RePEc:wbk:wbrwps:5983

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Keywords: Poverty Monitoring&Analysis; Science Education; Scientific Research&Science Parks; Economic Theory&Research; Housing&Human Habitats;

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  1. Das, Jishnu & Hammer, Jeffrey & Sanchez-Paramo, Carolina, 2011. "The impact of recall periods on reported morbidity and health seeking behavior," Policy Research Working Paper Series 5778, The World Bank.
  2. Chen, Shaohua & Mu, Ren & Ravallion, Martin, 2009. "Are there lasting impacts of aid to poor areas?," Journal of Public Economics, Elsevier, vol. 93(3-4), pages 512-528, April.
  3. Heike Solga, 2001. "Longitudinal Surveys and the Study of Occupational Mobility: Panel and Retrospective Design in Comparison," Quality & Quantity: International Journal of Methodology, Springer, vol. 35(3), pages 291-309, August.
  4. Sendhil Mullainathan & Marianne Bertrand, 2001. "Do People Mean What They Say? Implications for Subjective Survey Data," American Economic Review, American Economic Association, vol. 91(2), pages 67-72, May.
  5. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
  6. Elizabeth M. King & Jere R. Behrman, 2009. "Timing and Duration of Exposure in Evaluations of Social Programs," World Bank Research Observer, World Bank Group, vol. 24(1), pages 55-82, February.
  7. Crump, Richard K. & Hotz, V. Joseph & Imbens, Guido W. & Mitnik, Oscar A., 2006. "Moving the Goalposts: Addressing Limited Overlap in Estimation of Average Treatment Effects by Changing the Estimand," IZA Discussion Papers 2347, Institute for the Study of Labor (IZA).
  8. Anirudh Krishna & Daniel Lumonya & Milissa Markiewicz & Firminus Mugumya & Agatha Kafuko & Jonah Wegoye, 2006. "Escaping poverty and becoming poor in 36 villages of Central and Western Uganda," Journal of Development Studies, Taylor & Francis Journals, vol. 42(2), pages 346-370.
  9. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
  10. Ravallion, Martin & Chen, Shaohua, 2005. "Hidden impact? Household saving in response to a poor-area development project," Journal of Public Economics, Elsevier, vol. 89(11-12), pages 2183-2204, December.
  11. Ravallion, Martin & Lokshin, Michael, 2000. "Identifying welfare effects from subjective questions," Policy Research Working Paper Series 2301, The World Bank.
  12. Jalan, Jyotsna & Ravallion, Martin, 1998. "Are there dynamic gains from a poor-area development program?," Journal of Public Economics, Elsevier, vol. 67(1), pages 65-85, January.
  13. Eva Broegaard & Ted Freeman & Carsten Schwensen, 2011. "Experience from a phased mixed-methods approach to impact evaluation of Danida support to rural transport infrastructure in Nicaragua," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 3(1), pages 9-27.
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